Math @ Duke

Publications [#235519] of Pankaj K. Agarwal
Papers Published
 Agarwal, PK; Cheng, SW; Tao, Y; Yi, K, Indexing uncertain data,
Proceedings of the ACM SIGACTSIGMODSIGART Symposium on Principles of Database Systems
(2009),
pp. 137146 [doi]
(last updated on 2018/02/20)
Abstract: Querying uncertain data has emerged as an important problem in data management due to the imprecise nature of many measurement data. In this paper we study answering range queries over uncertain data. Specifically, we are given a collection P of n points in ℝ, each represented by its onedimensional probability density function (pdf). The goal is to build an index on P such that given a query interval I and a probability threshold t , we can quickly report all points of P that lie in I with probability at least t . We present various indexing schemes with linear or nearlinear space and logarithmic query time. Our schemes support pdf's that are either histograms or more complex ones such as Gaussian or piecewise algebraic. They also extend to the external memory model in which the goal is to minimize the number of disk accesses when querying the index. Copyright 2009 ACM.


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